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Real-world videos naturally portray complex interactions among distinct physical objects, effectively forming dynamic compositions of visual elements. However, most current video generation models synthesize scenes holistically and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Guofeng Zhang , Angtian Wang , Jacob Zhiyuan Fang , Liming Jiang , Haotian Yang , Alan Yuille , Chongyang Ma

Clonemator is a virtual reality (VR) system allowing users to create their avatar clones and configure them spatially and temporally, forming automators to accomplish complex tasks. In particular, clones can (1) freeze at a user's body pose…

Human-Computer Interaction · Computer Science 2023-11-09 Yi-Shuo Lin , Ching-Yi Tsai , Lung-Pan Cheng

Recent advances in foundational Video Diffusion Models (VDMs) have yielded significant progress. Yet, despite the remarkable visual quality of generated videos, reconstructing consistent 3D scenes from these outputs remains challenging, due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yisu Zhang , Chenjie Cao , Tengfei Wang , Xuhui Zuo , Junta Wu , Jianke Zhu , Chunchao Guo

Imitation learning has been applied to mimic the operation of a human cameraman in several autonomous cinematography systems. To imitate different filming styles, existing methods train multiple models, where each model handles a particular…

Computer Vision and Pattern Recognition · Computer Science 2019-12-24 Chong Huang , Yuanjie Dang , Peng Chen , Xin Yang , Kwang-Ting , Cheng

Camera calibration is an essential first step in setting up 3D Computer Vision systems. Commonly used parametric camera models are limited to a few degrees of freedom and thus often do not optimally fit to complex real lens distortion. In…

Computer Vision and Pattern Recognition · Computer Science 2020-06-24 Thomas Schöps , Viktor Larsson , Marc Pollefeys , Torsten Sattler

We propose ReCamDriving, a purely vision-based, camera-controlled novel-trajectory video generation framework. While repair-based methods fail to restore complex artifacts and LiDAR-based approaches rely on sparse and incomplete cues,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Yaokun Li , Shuaixian Wang , Mantang Guo , Jiehui Huang , Taojun Ding , Mu Hu , Kaixuan Wang , Shaojie Shen , Guang Tan

Aerial vehicles are revolutionizing the way film-makers can capture shots of actors by composing novel aerial and dynamic viewpoints. However, despite great advancements in autonomous flight technology, generating expressive camera…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Rogerio Bonatti , Arthur Bucker , Sebastian Scherer , Mustafa Mukadam , Jessica Hodgins

Generating videos guided by camera trajectories poses significant challenges in achieving consistency and generalizability, particularly when both camera and object motions are present. Existing approaches often attempt to learn these…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Guojun Lei , Chi Wang , Yikai Wang , Hong Li , Ying Song , Weiwei Xu

The need for automated real-time visual systems in applications such as smart camera surveillance, smart environments, and drones necessitates the improvement of methods for visual active monitoring and control. Traditionally, the active…

Computer Vision and Pattern Recognition · Computer Science 2021-07-29 Christos Kyrkou

We propose Camera Artist, a multi-agent framework that models a real-world filmmaking workflow to generate narrative videos with explicit cinematic language. While recent multi-agent systems have made substantial progress in automating…

Artificial Intelligence · Computer Science 2026-04-13 Haobo Hu , Qi Mao , Yuanhang Li , Libiao Jin

We present GEN3C, a generative video model with precise Camera Control and temporal 3D Consistency. Prior video models already generate realistic videos, but they tend to leverage little 3D information, leading to inconsistencies, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Xuanchi Ren , Tianchang Shen , Jiahui Huang , Huan Ling , Yifan Lu , Merlin Nimier-David , Thomas Müller , Alexander Keller , Sanja Fidler , Jun Gao

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control over four key video elements: foreground subject, background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Jingyun Liang , Jingkai Zhou , Shikai Li , Chenjie Cao , Lei Sun , Yichen Qian , Weihua Chen , Fan Wang

Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative capabilities. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Li Hu , Xin Gao , Peng Zhang , Ke Sun , Bang Zhang , Liefeng Bo

Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies while preserving frame quality remains challenging. Inspired by the human ability to leverage past…

In recent years, event cameras have gained significant attention due to their bio-inspired properties, such as high temporal resolution and high dynamic range. However, obtaining large-scale labeled ground-truth data for event-based vision…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yixuan Hu , Yuxuan Xue , Simon Klenk , Daniel Cremers , Gerard Pons-Moll

Generating rich and controllable motion is a pivotal challenge in video synthesis. We propose Boximator, a new approach for fine-grained motion control. Boximator introduces two constraint types: hard box and soft box. Users select objects…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Jiawei Wang , Yuchen Zhang , Jiaxin Zou , Yan Zeng , Guoqiang Wei , Liping Yuan , Hang Li

Recent progress in video diffusion models has spurred growing interest in camera-controlled novel-view video generation for dynamic scenes, aiming to provide creators with cinematic camera control capabilities in post-production. A key…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Min-Jung Kim , Jeongho Kim , Hoiyeong Jin , Junha Hyung , Jaegul Choo

Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing methods predominantly focus on camera control in perspective projection video generation, while…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Chenhao Ji , Chaohui Yu , Junyao Gao , Fan Wang , Cairong Zhao

Event cameras are novel sensors that output brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with respect to conventional cameras: high dynamic range (HDR),…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Daniel Gehrig , Mathias Gehrig , Javier Hidalgo-Carrió , Davide Scaramuzza
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